Summary
This website contacted 62 IPs in 6 countries across 20 domains to perform 81 HTTP transactions. The main domain is mays.tamu.edu and was registered NaN years ago.
Submitted URL: https://mays.tamu.edu/directory/ken-mcfarland/
The Cisco Umbrella rank of the primary domain is #27,424 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 96%
Legitimate university faculty page with no security concerns.
Safety Factors
Details
Page Title
Ken McFarland - Texas A&M University Mays Business School
Scan Type
public
Language
English
Category
corporate business
(49%)Domain Information
The domain name 'mays.tamu.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'mays'. The second-level label 'tamu' is 4 characters long containing two vowels alongside two consonants. Segmentation suggests 2 words: t, amu. Expect 2 characters per word on average. No strong language cues emerged from the frequency lists.
Screenshot
Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 32 | 141.193.213.11 | United States | AS209242Cloudflare London, LLC |
| 20 | 141.193.213.10 | United States | AS209242Cloudflare London, LLC |
| 6 | 216.58.212.136 | United States | AS15169GOOGLE |
| 5 | 52.242.103.142 | Boydton, Virginia, United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 142.250.186.35 | United States | AS15169GOOGLE |
| 4 | 142.250.185.131 | United States | AS15169GOOGLE |
| 3 | 150.171.22.12 | United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 3 | 142.250.185.68 | United States | AS15169GOOGLE |
| 3 | 157.240.0.35 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 3 | 216.239.32.36 | United States | AS15169GOOGLE |
| 81 | 62 | - | - |
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.
Image Hashes
Perceptual Hashes
Other Hashes
Scan History
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